DeepLiveCam
Open-source, local AI tool for real-time face swaps and video avatar creation.
What is DeepLiveCam?
Deep-Live-Cam is an open-source, privacy-first AI tool designed specifically for VTubers, streamers, and video creators to perform stunning real-time face swaps and avatar creation with zero coding required. Operating as a completely local application, it enables users to seamlessly go live as anyone or anything without worrying about data tracking. For those looking to upgrade their stream setup, the deep live cam app offers direct integration with broadcasting tools like OBS, functioning similarly to deepfacelive but engineered for simple, single-image execution. Users frequently seek out a reliable deep live cam install to experience its advanced parallel multi-face mapping, realistic mouth masking for lip-syncing, and standard video face-swapping capabilities. With recent performance enhancements rolled out in deep live cam 2.1 and the stable v2.0 releases, deeplivecam.net serves as the official platform for software distribution and hardware-optimized subscription plan management.
Best DeepLiveCam use cases by task, role, industry, and platform
These use cases show where DeepLiveCam fits best, ranked by fit score before popularity or pricing.
DeepLiveCam Pricing Plans
Compare DeepLiveCam free options, DeepLiveCam paid pricing plans, and usage notes before you choose the best way to use this AI tool in 2026.
Paid subscription required for GPU-optimized binaries
Provides software download access optimized for NVIDIA graphics cards. Requires Windows 10+, a minimum of 6GB VRAM (RTX 3060 or higher recommended), and a pre-installed CUDA 11.8 environment.
Provides software download access optimized for AMD graphics cards. Requires Windows 10+ and a recommended minimum of 6GB VRAM.
Pricing updated:Jun 11, 2026
DeepLiveCam AI Features
DeepLiveCam Pros and Cons
Pros
- Completely local execution ensures total data privacy and zero data collection
- No coding required thanks to a new user-friendly self-extracting archive and simple UI
- Open-source code base publicly available for auditing on GitHub
- Eliminates blurry outputs with newly integrated transparency and sharpening features
- Supports multi-subject parallel face mapping in a single inference session
Limitations
- Highly hardware-dependent; frame rates drop below 10 FPS (as low as 0.5 FPS) with face enhancement on weak systems
- Requires manual pre-installation of specific external dependencies like CUDA 11.8 for Nvidia setups